Course Description:
This webinar will help the attendee understand the sources of uncertainty and variability in industrial hygiene data, and how to choose a statistical analysis tool, particularly when only a few samples are collected. The strengths and limitations of three statistical approaches - traditional statistics, Bayesian statistics, and rule-based statistics – are compared through the application of real-world and modeled data. Because of the uncertainty and variability in typical industrial hygiene data sets, there are common pitfalls in interpreting the data, even among experienced industrial hygienists. Traditional and advanced statistical tools are under-utilized and often misunderstood and misapplied. The appropriate choice and use of each tool depend on the circumstances and data.

Learning Objectives:
Upon completion, participants will be able to:

• Understand sources of uncertainty and variability in industrial hygiene data
• Identify strengths and limitations of statistical approaches to analyzing industrial hygiene data
• Avoid common pitfalls in applying statistics to industrial hygiene data
• Choose the right statistical tools to analyze industrial hygiene data

Contact Hours:
1

Presentation Date:
04/24/2018

Presenters:
Brent Altemose